Some "Statistical Visualizations" for your projects

In this project, we will se how to create plot and graphic visualizations that are useful for your own data science projects.

There are 4 tasks to implement our project:

Task 1: Learning Practical Basic Statistics.

Task 2: Learning Statistical Visualization with Seaborn.

Task 3: Learning Statistical Visualization with Plotly.

Task 4: Learning Statistical Visualization with Matplotlib.

Task 1: Basic Statistics

Task 2: Statistical Visualization with Seaborn

Timeseries plot with error bands

Plotting with date data

Scatterplot Matrix

Scatterplot with categorical and numerical semantics

Horizontal boxplot with observations

Linear regression with marginal distributions

Plotting on a large number of facets

Task 3: Statistical Visualization with Plotly

Creating Box Plots

Creating Histograms

Creating Dist Plots

Creating Density Heatmaps

Creating Violin Plots

Creating Linear and Non-Linear Trendlines

Creating Scatterplot Matrix

Task 4: Statistical Visualization with Matplotlib

Creating Boxplots with Custom fill colors

Creating Error Bars

Creating histograms for cumulative distribution

Creating Violin Plots